Tracking Soft Tissue in Medical Images

ABSTRACT

The present disclosure is directed to a system, method and apparatus for tracking an anatomical body part in a series of x-ray images. The anatomical body part moves due to a vital movement, such as breathing motion of the thorax. The anatomical body part is defined in a CT image acquired beforehand and is associated with a known movement phase during the vital movement. The series of x-ray images of the moving anatomical body part is taken. The movement phase associated with each one of the x-ray images is determined. In one implementation, the system may track the body part movement using external infrared-reflecting markers and a navigation system while taking a series of x-ray images and time-stamping the x-ray images and the positional information for the body part. The time stamps relate each one of the x-ray images with a specific movement phase of the body part. The specific x-ray image being associated with the same movement phase as the CT image is determined and the representation of the anatomical body part defined in the CT image can be determined in the x-ray image by comparing the CT image with the specific x-ray image. The specific x-ray image may be compared to the other x-ray images to find the anatomical body part in those x-ray images and preferably highlight it to be easily recognized by a user.

The present invention relates to a medical data processing method ofdetermining the representation of an anatomical body part of a patientin a sequence of medical images, wherein the anatomical body part issubject to a vital movement of the patient. The data processing methodis preferably constituted to be executed by a computer. The inventiontherefore also relates to a corresponding computer program and acomputer executing that program.

When executing medical procedures such as radiosurgery or radiotherapyin particular outside of the head (so-called extra-cranial radiosurgeryor radiotherapy), for example in order to deliver a desired radiationdose to a target region including in particular a tumour which islocated in soft tissue (such as lung tissue or tissue of other internalorgans), it is in general necessary to consider a vital movement of sucha target region in order to support continuous irradiation of the targetregion and avoid irradiation of off-target regions such as organs atrisk which shall not be damaged. Such vital movements are in particularperiodic and due to fro example a shift of organ tissue caused by forexample breathing motion of the thorax, the beating motion of the heartor movements of other internal organs such as the intestines. Furtherexplanations as to the origin and consequences of vital movements arealso disclosed in EP 2 189 943 A1 and EP 2 189 940 A1, also published asUS 2010/0125195 A1 and US 2010/0160836 A1, respectively.

When conducting one of for example the aforementioned medicalprocedures, it is often desirable to have a visual guidance for theposition of the soft tissue which is subject to the vital movement.

In this regard, the “Xsight Lung Tracking System” produced by AccurayInc. provides for a superposition and fusion, respectively, of DRRs tocorresponding X-ray images in order to compare the current position ofthe soft tissue to be tracked (defined by the X-ray images) with itsplanned position (defined by the DRRs which are gathered from apre-acquired planning computed tomography). However, visually inspectingthe fusion between a digitally rendered radiograph (DRR) that focuses onsoft tissue and a conventional X-ray image is difficult andtime-consuming, and thus hardly feasible without applying an automatedprocess. Furthermore, such an automatic multi-modal fusion (i.e. fusionbetween images generated by applying different medical imagingmodalities) lacks robustness. Besides that, the information contained inthe DRRs is out of date and therefore a comparison of each one of aplurality of DRRs with a (single) X-ray image may lead to erroneousresults.

The following documents are of general relevance to the field oftechnology to which the present invention relates: US 2008/00337843 A1,U.S. Pat. No. 6,501,981 B1, U.S. Pat. No. 6,144,875 A.

A problem to be solved by the present invention therefore is to providean improved method and apparatus for tracking the position of movingsoft tissue in a series of X-ray images.

This problem is solved by the subject-matter of any appended independentclaim. Advantages, advantageous features, advantageous embodiments andadvantageous aspects of the present invention are disclosed in thefollowing and contained in the subject-matter of the dependent claims.Different advantageous features can be combined in accordance with theinvention wherever technically expedient and feasible. Specifically, afeature of one embodiment which has the same or a similar function toanother feature of another embodiment can be exchanged with said otherfeature, and a feature of one embodiment which adds an additionalfunction to another embodiment can in particular be added to said otherembodiment.

The present invention shall primarily be used in particular within theVero® radiosurgery system provided by Brainlab AG. Vero® provides highaccuracy for treatment delivery, even with moving targets. Corefeatures, such as sophisticated and versatile image-guidance,verification tools and the first-of-its-kind gimbaled irradiation headwith tilt functions for isocentric and non-isocentric treatments delivertargeting confidence. With built-in fluoroscopy, tumor areas can betreated dynamically in real time even as they move in parallel withbreathing and digestion with uninterrupted beam delivery. Vero®possesses an innovative imaging feedback system to deliver high quality,targeted and truly individualized treatments. Furthermore, Vero®provides the following advantageous capabilities:

-   -   Enables confident treatment of moving targets and high accuracy        dose delivery    -   Motion management with versatile image guidance and verification        tools and gimbaled irradiation head with tilt functions for        isocentric and non-isocentric treatments    -   Uninterrupted dynamic moving tumor treatment with proprietary        real-time stereo fluoroscopy    -   Targeted, individualized delivery of treatments with continuous        tracking; incorporates anatomical changes and breathing cycles        with closed-loop feedback system

EXEMPLARY SHORT DESCRIPTION OF THE PRESENT INVENTION

In the following, a short description of specific features of thepresent invention is given which shall not be understood to limit theinvention only to the features or a combination of the featuresdescribed in this section.

The present invention is directed in particular to a data processingmethod (e.g. a computer program) for tracking an anatomical body part,such as the diaphragm or a tumour, in a series of x-ray images. Theanatomical body part moves due to e.g. a vital movement such asbreathing motion of the thorax. The anatomical body part is defined in aCT image acquired beforehand and being associated with a known movementphase (e.g. full inspiration or full expiration) during the vitalmovement. Then, the series of x-ray images of the (still moving)anatomical body part is taken. An aim of the invention is to track andadvantageously visually highlight the anatomical body part throughoutthe series of x-ray images. A problem may, however, occur in doing sosince the representation (e.g. visual impression) of the anatomical bodypart may not be comparable between the pre-acquired CT image and anarbitrary one of the series of x-ray images. Thus, the movement phaseassociated with each one of the x-ray images is determined. According toone solution, this is done by tracking the thoracic movement usingexternal infrared-reflecting markers and a navigation system whiletaking the series of x-ray images and time-stamping the x-ray images andthe positional information for the thorax gathered from tracking. Thetime stamps relate each one of the x-ray images with a specific movementphase of the thorax. The specific x-ray image being associated with thesame movement phase as the CT image can therefore be determined, and therepresentation of the anatomical body part defined in the CT image canbe determined in the x-ray image by comparing the CT image with thespecific x-ray image, for example by fusing the CT image to the specificx-ray image. The specific x-ray image is then compared to the otherx-ray images (e.g. by fusing the specific x-ray image to the other x-rayimages) to find the anatomical body part in those x-ray images andpreferably highlight it to be easily recognized by a user.

The invention also relates to a computer configured to execute acorresponding computer program. Furthermore, the invention relates to atreatment device (for example, a radiotherapy device or radiosurgerydevice) comprising such a computer.

GENERAL DESCRIPTION OF THE PRESENT INVENTION

In this section, a description of the general, in particular preferred,features of the invention is given.

In order to solve the aforementioned problem, in particular a dataprocessing method, more particularly a medical data processing method(i.e. a data processing method for use in relation to a medicalenvironment), of determining the representation of an anatomical bodypart of a patient in a sequence of medical images is provided. Theanatomical body part is subject to in particular a vital movement of thepatient (i.e. of a vital movement of at least one body part of thepatient) and may be any anatomical body part. In particular, theanatomical body part comprises a tumour and may therefore constitute atarget region on which the envisaged medical procedure such asradiotherapy or radiosurgery may be carried out. In particular, theanatomical body part represents a soft tissue body part such as skin, ortissue constituting an internal organ such as the stomach, the heart,the liver, the diaphragm or the lung. A soft-tissue body part differsfrom a hard tissue body part (such as bone or cartilage) in particularin respect of its absorption for imaging radiation (such aselectromagnetic waves in the magnetic resonance spectrum used formagnetic resonance imaging, ultrasound imaging radiation or ionizingimaging radiation such as x-rays). In general, the absorption of forexample ionizing imaging radiation is lower in soft tissue than in hardtissue.

The method is preferably constituted to be executed by a computer. Inparticular, the computer may execute all or less than all of the stepsof the disclosed method. Preferably, at least one step of the disclosedmethod is executed by a computer. The disclosed method comprises thefollowing preferable steps and features.

Preferably, advance medical image data is acquired which comprises atime-related advance medical image. The advance medical image comprisesand in particular defines (more particularly, represents and/or is) arepresentation of the anatomical body part in a specific movement phase.The advance medical image preferably is time-related, i.e. the imageinformation contained in the advance medical image is associated withtime information such as a point in time, for example absolute time orrelative to a specific starting point in time. The specific movementphase corresponds to a specific movement state in the vital movementwhich the anatomical body part is subject to. In particular, theanatomical body part moves due to the vital movement and thereby passesthrough a plurality of movement states during the vital movement. Sincethe vital movement is in particular cyclic (periodic), each movementstate may be associated with a specific movement phase. For example, theanatomical body part is the diaphragm which is subject to the thoracicbreathing movement as a vital movement. A specific movement phase maythen define states of e.g. inspirational movement or expirationalmovement (for example a specific movement phase may be completeinspiration or complete expiration). The advance medical image istime-related in order to associate the representation of the anatomicalbody part with the specific movement phase.

Preferably, the advance medical image data has been generated inparticular before execution of the disclosed method by detecting thevital movement for example based on tracking marker devices attached tothe patient's body and correlating the result of the tracking (i.e. theresulting positional measurements) with medical image data serving as abasis for generating the advance medical image, for example with apre-acquired computed tomography which is used in particular forplanning the envisaged medical procedure to be carried out on thepatient). The markers are preferably retroreflective markers which areable to reflect infrared electromagnetic radiation, the reflectionsbeing detected by a detection unit (e.g. a stereoscopic camera) of anavigation system and transformed into digital signals which indicatethe positions of the markers. For example, the vital movement is theaforementioned breathing movement and the anatomical body part is thediaphragm. A breathing curve of the breathing movement of the diaphragmis generated for example by attaching retroreflective markers to thepatient's thorax and acquiring a sequence of computed tomography (CT)images while tracking and recording the positions and/or positionalchanges of the markers during the breathing movement. Thereby, eachrepresentation of the diaphragm in a single CT image may be associatedwith a specific movement state (i.e. in particular position) of themarkers and thereby specific movement phase of the diaphragm. Thebreathing curve then describes (in particular represents) the positionof the thorax (in particular, its geometry, for example volume) independence on time. In particular, the advance medical image isassociated with a specific point (in particular point in time) on thebreathing curve. Further particularly, the advance medical image isassociated with a specific movement phase in the period of the vitalmovement, i.e. in the breathing period. The term of marker and how theposition of a marker can be determined is explained further below in thesection “Definitions”.

The advance medical image preferably is at least one digitally renderedradiograph (DRR), in particular a pair of digitally rendered radiographs(DRRs), rendered from a CT image of the anatomical body part. In thiscontext, the term of “image” encompasses also a pair of images which areoriented in viewing directions which are preferably perpendicular toeach other.

In the framework of the present disclosure, the term of representationencompasses the visual impression which the anatomical body partgenerates in a specific image (for example, in the advance medical imageor the current medical image or the tracked image subset or the trackingcurrent medical image which are mentioned below). The term ofrepresentation therefore encompasses graphic, in particular geometricand colour features, of the image of the anatomical body part. Forexample, the term of representation encompasses contrast values, andcolours in the respective medical image.

Preferably, current medical image data is acquired which describes (inparticular defines, more particularly represents and/or comprises) asequence of current medical images. The current medical images arepreferably x-ray images (generated for example using a fluoroscope, andthus representing a sequence of fluoroscopic x-ray images). The currentmedical images preferably are each at least one (e.g. fluoroscopic)x-ray image (as an example, each current medical image comprises, inparticular consists of, a pair of stereo-x-ray images) of the anatomicalbody part. In this context, the term of “image” encompasses also a pairof images which are oriented in viewing directions which are preferablyperpendicular to each other. The sequence comprises a specific currentmedical image, in particular at least one such specific current medicalimage. The current medical image comprises (in particular defines, moreparticularly represents and/or is) a representation of the anatomicalbody part in the specific movement phase. The specific movement phase isat least substantially the same as (i.e. in a preferred embodiment, itis the same as and/or identical to) the specific movement phase definedby the representation of the anatomical body part in the advance medicalimage. The current medical image data furthermore describes (inparticular defines, more particularly represents and/or comprises) atleast one tracking current medical image, preferably a plurality oftracking current medical images. Each tracking current medical image ispreferably different from the specific current medical image, andcomprises (in particular defines, more particularly represents and/oris) a representation of the anatomical body part in the movement phase(also called tracking movement phase) which is different from thespecific movement phase. In particular, the tracking movement phase andthe specific movement phase are not identical.

Preferably, the advance medical image data has been generated byapplying a computed tomography imaging method to the patient's body andthe advance medical image is in particular a digitally renderedradiograph rendered from the computer tomography of the patient's body.Further preferably, the sequence of current medical images has beengenerated by applying an x-ray imaging method (in particular aconventional x-ray imaging method) such as a stereo-x-ray-imaging method(e.g. using the aforementioned fluoroscope) to the patient's body.However, it is also within the framework of this disclosure that thesequence of current medical images (i.e. both the at least one specificcurrent medical image and the at least one tracking current medicalimage) have been generated by another medical imaging method, inparticular not by x-ray imaging.

Preferably, specific image subset data is determined based on the (inparticular from) the advance medical image data and the current medicalimage data. The specific image subset data describe (more particularly,represents and/or is) in particular a specific image subset of thespecific current medical image. The image subset is preferably a “real”subset of the specific current medical image, i.e. it comprises (inparticular consists of, i.e. comprises only) image information from thespecific current medical image which is less than the total imageinformation contained in the specific current medical image. However,the image subset comprises at least the representation of the anatomicalbody part in the specific medical image. The current medical image ispreferably determined by comparing the advance medical image to thesequence of current medical images and finding the current medical imagecomprising a representation of the anatomical body part which bestmatches the representation of the anatomical body part in the advancemedical image. It is general to be assumed that this best match isachieved when the anatomical body part in the representation of theadvance medical image and in the representation of the current medicalimage has the same movement state, and if specific current medical imageand the advance medical image describe in particular the same (namelythe specific) movement phase.

Preferably, the specific image subset data is determined for exactly one(i.e. only one) of the current medical images. This approach allows foran efficient procedure in first of all determining the image region inthe specific current medical image to be tracked and by applyingknowledge about this region to the at least one tracking current medicalimage.

The comparison between the sequence of current medical images and theadvance medical images is preferably performed by applying an imagefusion algorithm to the advance medical image and the sequence ofcurrent medical images to find the specific current medical image, i.e.the member of the sequence of current medical images which best fits tothe advance medical image based on fusing the advance medical image toeach one of the sequence of current medical images. The image fusionalgorithm may be constituted to conduct an elastic or a rigid imagefusion. Elastic image fusion allows for deformation of geometries, rigidimage fusion does not involve a deformation of geometry. In particular,the specific current medical image is the member of the sequence of thecurrent medical images which is most similar to the advanced medicalimage. The terms of image fusion and similarity are explained furtherbelow in the section “Definitions” within the explanation relating toimage fusion. In order to successfully perform the image fusion betweenthe advance medical image and the sequence of current medical images, itis preferred that the current medical image data and the advance medicalimage data have been generated by applying a medical imaging modalityfor generating the respective dataset which in the case of both datasetsunderlies the at least substantially same absorption of the imagingradiation by the anatomical body part. For example, the advance medicalimage data has been generated by applying an x-ray-based computedtomography imaging modality, and the current medical image data has beengenerated by applying an x-ray imaging modality. Since both thesemodalities use x-rays for imaging the anatomical body part, theabsorption values of the imaging radiation is comparable if not the samein both the case of generating the advance medical image data and thecurrent medical image data.

Preferably, the specific image subset data is determined based on (inparticular by) in particular automatically or manually determining acorresponding representation of the anatomical body part in the advancemedical image and the specific current medical image. Correspondingrepresentation in this sense means that the representations of theanatomical body part in both images are similar to each other at leastto a predetermined extent. This similarity is determined as explainedabove according to one specific embodiment automatically determined byapplying an image fusion algorithm to the advance medical image and thespecific current medical image. A region in the specific current medicalimage for which the similarity has been determined is then for exampleselected and in particular outlined and/or highlighted in the specificcurrent medical image.

According to an alternative and specific preferred embodiment, currentmedical image user input data is acquired which describes (in particulardefines and/or represents) an input (in particular information gatheredfrom an input) by a user. The input is for example a manual input.Furthermore, the input is suitable for selecting the specific imagesubset from the specific current medical image. For example, the usermay operate a touchscreen to delimit the specific image subset from thespecific current medical image which has beforehand been determined tocontain the representation of the anatomical body part which is (withinthe sequence of current medical images) most similar to therepresentation of the anatomical body part in the advance medical image.Alternatively or additionally, the user may operate a pointing and inputequipment for selecting the specific image subset, such as mouse or atrackball to define the specific image subset on a visual indicatingmeans such as a monitor displaying the specific current medical image.The selected image information defines the specific image subset (inparticular, the specific image subset consists of the clipped imageinformation).

According to an alternative embodiment, advance image subset data isacquired which describes an advance image subset of the imageinformation contained in the advance medical image. As explained withregard to the specific image subset, the advance image subset also is a“real” subset of the advance medical image. In particular, the advanceimage subset comprises (in particular consists of, i.e. comprises only)image information contained in the advance medical image and less imageinformation than the total image information contained in the advancemedical image. The advance image subset comprises the representation ofthe anatomical body part in the advance medical image. The advance imagesubset data can also be generated and acquired on the basis of userinput as explained with regard to the current medical image user inputdata. In the case of user input for acquiring the advance image subsetdata, preferably advance medical image user input data is acquired whichdescribes the required input by a user. The details of such a user inputare in particular the same as for the user input used for acquiring thecurrent medical image user input data with the exception that the userinput is executed on the advance medical image and not on the specificcurrent medical image. The advance image subset data is then determinedbased on the advance medical image user input data.

As an alternative to user input for defining the specific image subsetand/or the advance image subset, at least one (preferably both) of theadvance image subset and the specific image subset can be determined byapplying an image segmentation algorithm (for example, an edge detectionalgorithm) to the respective one of the advance medical image and/or thespecific current medical image. As an even further feature, the specificimage subset can be determined by matching the current medical imagedata with an atlas, e.g. by image fusion between the current medicalimage data and an atlas. An atlas is understood to be a model of apatient's body which has been generated by statistical analysis ofmedical images taken for a plurality of patient bodies. For example, ananatomical body part to be included in the specific image subset can bedefined in the atlas and the current medical image data can be matchedwith the atlas to determine the specific image subset which includes therepresentation of that anatomical body part. The anatomical body partmay be for example an indicator body part indicating the specificmovement phase (e.g. the diaphragm if the vital movement is a breathingmovement). In an even further embodiment, matching the atlas with thecurrent medical image data can be combined with a user input or an imagesegmentation algorithm for defining the specific image subset. Forexample, that matching with the atlas may be conducted subsequently tothe user input or to execution of the image segmentation algorithm inorder to check whether the specific image subset thus determinedactually includes a representation of the anatomical body part selectedfrom (in) the atlas.

It is notable that the above-described embodiments for using user inputor automatic determination for defining the advance image subset and/orthe specific image subset may also be combined. For example, first anautomatic determination of the advance image subset and/or the specificimage subset may be performed, followed by a manual correction of theautomatic determination result (e.g. of the segmentation result) by userinput. For example, the user may wish to increase or decrease the extentof the specific image subset and/or the advance image subset.

The specific image subset data may according to a further embodimentalso be determined based on the result of comparing the advance imagesubset to the specific current medical image. For example, an imagefusion algorithm may be applied to the specific image subset to fuse itto the specific current medical image (i.e. an image fusion algorithmmay be applied to the advance image subset data and the current medicalimage data describing—in particular defining, more particularlyrepresenting and/or being—the specific current medical image) in orderto determine the region in the specific current medical image which ismost similar to the advance image subset. Thereby, the specific imagesubset is determined.

Preferably, subset tracking data is determined based on (in particularfrom) the current medical image data and the image subset data. Thesubset tracking data describes (in particular defines, more particularlyrepresents and/or is) a tracked image subset in the tracking currentmedical image. The tracked image subset comprises (in particulardefines, more particularly represents and/or is) the representation ofthe anatomical body part in the tracking current medical image. In thecase of the current medical image data describing more than one trackingcurrent medical image, the tracked image subset is determined for eachone of the tracking current medical images. For example, the sequence ofcurrent medical images (in particular, all current medical images whichare not identical to the specific current medical image) are searchedfor image information which is at least to a predetermined extentcomparable (in particular similar) to the specific image subset. Forexample, the specific image subset data can be fused (by conducting anelastic or rigid image fusion algorithm) to the other members of thesequence of the current medical images (in particular to the at leastone tracking current medical image) in order to determine a region inthe tracking current medical image which contains the representation ofthe anatomical body part which is at least to a predetermined degreecomparable (in particular similar) to the specific image subset. Thisregion then is determined to be the tracked image subset.

Preferably, the specific image subset data describes (in particularcontains information defining, more particularly representing and/orbeing) the position of the specific image subset in the specific currentmedical image. Further preferably, the subset tracking data describes(in particular contains information defining, more particularlyrepresenting and/or being) the position of the tracked image subset inthe tracking current medical image. In particular, the specific imagesubset data and the subset tracking data, respectively, containinformation defining the pixel coordinates of the specific image subsetand the tracked image subset, respectively, in the specific currentmedical image and the tracking current medical image, respectively. Thisallows to extract the medical image information making up the specificimage subset from the specific current medical image in order to performthe comparison with (in particular fusion to) the at least one trackingcurrent medical image for determining the tracked image subset. Inparticular, positions (i.e. pixel coordinates) in the tracking currentmedical image having the same values as the position (i.e. pixelcoordinates) of the specific image subset are analyzed with respect tothe degree of similarity to the specific image subset. Alternatively,the specific image subset may be compared to the total image informationcontained in the tracking current medical image in order to determinethe region in the tracking current medical image which fulfills theconditions for similarity to the specific image subset. In thisapproach, it is not necessary to know the position of the specific imagesubset in the specific current medical image. Therefore, the trackingcurrent medical image is searched for a region which is similar to thespecific image subset. In other words, the subset tracking data isdetermined preferably by determining a region in the tracking currentmedical image which is at least to a predetermined degree comparable tothe specific image subset.

The disclosed method comprises a further preferred step of determiningdisplay marking data based on (in particular from) the specific imagesubset data and the tracking image subset data. The display marking datadescribes (in particular defines, more particularly represents and/oris) a graphical feature for marking the positions of the specific imagesubset and the tracking image subset in particular a graphical renderingof the specific current medical image and the tracking current medicalimage, respectively. This allows for supplying the user with visualinformation such as for example a frame which is highlighted around theanatomical body part so as to simplify visual tracking of its vitalmovement.

Preferably, the disclosed method comprises a step of determininginternal breathing curve data based on (in particular from) the currentmedical image data and the subset tracking data and current movementphase data. The properties of the current movement phase data shall bedescribed further below. The internal breathing curve data describes (inparticular defines, and more particularly represents and/or is) atime-correlation of the image positions of the anatomical body part andthe sequence of medical images. In particular, each one of the sequenceof the medical images is assigned to a specific movement phase of theanatomical body part. Thereby, an internal breathing curve of theanatomical body part can be established by having a (in particular onlyone) advance medical image which is associated with a known specificmovement phase of the anatomical body part, finding the correspondingcurrent medical image under the assumption that it is associated alsowith the specific movement phase, and tracking the representation of theanatomical body part in that current medical image in the other membersof the sequence of current medical images (i.e. in the at least onetracking current medical image).

In an advantageous embodiment, generation of the internal breathingcurve data is supported by acquiring the aforementioned current movementphase data. The current movement phase data describes (in particulardefines, more particularly represents and/or is) a current movementphase of the anatomical body part in the states in which it is described(i.e. depicted) by the sequence of current medical images. The currentmovement phase data is generated for example based on (in particular by)acquiring digital signals which describe the vital movement. Suchdigital signals have been generated preferably based on (in particularby) for example tracking marker devices attached to the patient's bodyand correlating (in particular time-correlating) the result of thetracking (i.e. the positional measurements gained thereby) with thecurrent medical image data. In particular, each one of the currentmedical images is associated with a specific point on the movement curvedefining the vital movement, in the case of the vital movement being thebreathing movement of the patient, for example on the breathing curve.The specific current medical image is then preferably determined basedon the current movement phase data. In particular, the time informationwith which the current medical image data is associated serves as abasis for selecting the current medical image (i.e. the specific currentmedical image) which is associated with the same movement phase as theadvance medical image, i.e. with the specific movement phase (definingthe same point on the vital movement curve, for example on the breathingcurve). This avoids having to assert the whole sequence of the currentmedical images for a representation of the anatomical body part in thespecific movement phase in order to determine the specific currentmedical image.

The current medical image data is according to an alternative embodimentof the disclosed method not acquired while tracking a vital movementusing markers and a navigation system for tracking the markers. Rather,the current medical image data is acquired at specific (discrete) pointsin time during a cycle of the vital movement, for example during onebreathing cycle (breathing period) in the case of the vital movementbeing a breathing movement. Thus, it is ensured that the current medicalimage data comprises a representation of the anatomical body part inboth the specific movement phase and the tracking movement phase. Theexplanations regarding the technical meaning of the specific movementphase are in general also valid for the tracking movement phase with theexception that the tracking movement phase is not identical to thespecific movement phase.

The inventions provides the advantage of being able to track a movinganatomical body part in a series of x-ray images outgoing from a CTimage of the anatomical body part without having to conduct a pluralityof image fusion procedures between images of different medical imagingmodalities (i.e. multi-modal image fusions, which are known to becomplicated and prone to data processing faults), i.e. between aplurality of CT images and each at least one x-ray image. Rather, such amulti-modal image fusion is conducted only once between the advancemedical image and at least one current medical image (e.g. an x-rayimage), preferably only one current medical image which is known to bethe specific current medical image from e.g. tracking the patient'svital movement while generating the current medical image data).Tracking the anatomical body part in the remaining images of thesequence of current medical images (x-ray-images) is then done byconducting mono-modal image fusion procedures between the currentmedical images (e.g. between the specific current medical image and theat least one tracking current medical image) which were all generatedusing the same medical imaging modality (namely x-ray). Thereby,problems associated with conducting multi-modal image fusion areavoided.

The invention also relates to a program which, when running on acomputer, causes the computer to perform one or more or all of themethod steps described herein and/or relates to a program storage mediumon which the program is stored (in particular in a non-transitory form)and/or relates to a computer comprising said program storage mediumand/or relates to a (physical, in particular electrical, in particulartechnically generated) signal wave, in particular a digital signal wave,carrying information which represents the program, in particular theaforementioned program, which in particular comprises code means whichare adapted to perform any or all of the method steps described herein.

The invention also relates to a treatment device, which is at least oneof for example a radiotherapy device and a radiosurgery device,comprising:

-   -   a) the aforementioned computer which is in particular configured        to execute the aforementioned program which, when running on the        computer or when loaded onto the computer (in particular into        the memory of the computer), causes the computer to perform the        method steps of the above-described method;    -   b) a medical imaging device for acquiring the current medical        image data, wherein the medical imaging device is for example an        x-ray imaging device or a CT imaging device (a computer        tomograph);    -   c) an irradiation unit for emitting a treatment beam to the        patient's body, wherein the irradiation unit is at least one of        a particle accelerator, a high-energy x-ray-tube and a        radioactive substance which emits preferably gamma radiation.

The computer of the radiotherapy and/or radiosurgery device ispreferably operatively coupled to the medical imaging device to acquirethe current medical image data.

Furthermore, it is preferably operatively coupled to the irradiationunit to issue control signals to the irradiation unit for emitting thetreatment beam. In particular, the computer is configured to activatethe irradiation unit based on the current movement phase data. Forexample, the computer may determine whether the current movement phasedata indicates that the current movement phase is a predeterminedmovement phase at which the target region (which according to aparticular embodiment coincides with the anatomical body part) shall beirradiated, and the treatment beam is then activated.

In particular, the invention does not involve or in particular compriseor encompass an invasive step which would represent a substantialphysical interference with the body requiring professional medicalexpertise to be carried out and entailing a substantial health risk evenwhen carried out with the required professional care and expertise. Inparticular, the invention does not comprise a step of positioning amedical implant in order to fasten it to an anatomical structure or astep of fastening the medical implant to the anatomical structure or astep of preparing the anatomical structure for being fastened to themedical implant. More particularly, the invention does not involve or inparticular comprise or encompass any surgical or therapeutic activity.The invention is instead directed in particular to positioning the toolrelative to the medical implant, which may be outside the patient'sbody. For this reason alone, no surgical or therapeutic activity and inparticular no surgical or therapeutic step is necessitated or implied bycarrying out the invention.

Definitions

In this section, definitions for specific terminology used in thisdisclosure are offered which also form part of the present disclosure.

Within the framework of the invention, computer program elements can beembodied by hardware and/or software (this includes firmware, residentsoftware, micro-code, etc.). Within the framework of the invention,computer program elements can take the form of a computer programproduct which can be embodied by a computer-usable, in particularcomputer-readable data storage medium comprising computer-usable, inparticular computer-readable program instructions, “code” or a “computerprogram” embodied in said data storage medium for use on or inconnection with the instruction-executing system. Such a system can be acomputer; a computer can be a data processing device comprising meansfor executing the computer program elements and/or the program inaccordance with the invention, in particular a data processing devicecomprising a digital processor (central processing unit or CPU) whichexecutes the computer program elements, and optionally a volatile memory(in particular a random access memory or RAM) for storing data used forand/or produced by executing the computer program elements. Within theframework of the present invention, a computer-usable, in particularcomputer-readable data storage medium can be any data storage mediumwhich can include, store, communicate, propagate or transport theprogram for use on or in connection with the instruction-executingsystem, apparatus or device. The computer-usable, in particularcomputer-readable data storage medium can for example be, but is notlimited to, an electronic, magnetic, optical, electromagnetic, infraredor semiconductor system, apparatus or device or a medium of propagationsuch as for example the Internet. The computer-usable orcomputer-readable data storage medium could even for example be paper oranother suitable medium onto which the program is printed, since theprogram could be electronically captured, for example by opticallyscanning the paper or other suitable medium, and then compiled,interpreted or otherwise processed in a suitable manner. The datastorage medium is preferably a non-volatile data storage medium. Thecomputer program product and any software and/or hardware described hereform the various means for performing the functions of the invention inthe example embodiments. The computer and/or data processing device canin particular include a guidance information device which includes meansfor outputting guidance information. The guidance information can beoutputted, for example to a user, visually by a visual indicating means(for example, a monitor and/or a lamp) and/or acoustically by anacoustic indicating means (for example, a loudspeaker and/or a digitalspeech output device) and/or tactilely by a tactile indicating means(for example, a vibrating element or a vibration element incorporatedinto an instrument). For the purpose of this document, a computer is atechnical computer which in particular comprises technical, inparticular tangible components, in particular mechanical and/orelectronic components. Any device mentioned as such in this document isa technical and in particular tangible device.

The method in accordance with the invention is in particular a dataprocessing method. The data processing method is preferably performedusing technical means, in particular a computer. The data processingmethod is preferably constituted to be executed by or on a computer andin particular is executed by or on the computer. In particular, all thesteps or merely some of the steps (i.e. less than the total number ofsteps) of the method in accordance with the invention can be executed bya computer. The computer in particular comprises a processor and amemory in order to process the data, in particular electronically and/oroptically. The calculating steps described are in particular performedby a computer. Determining steps or calculating steps are in particularsteps of determining data within the framework of the technical dataprocessing method, in particular within the framework of a program. Acomputer is in particular any kind of data processing device, inparticular electronic data processing device. A computer can be a devicewhich is generally thought of as such, for example desktop PCs,notebooks, netbooks, etc., but can also be any programmable apparatus,such as for example a mobile phone or an embedded processor. A computercan in particular comprise a system (network) of “sub-computers”,wherein each sub-computer represents a computer in its own right. Theterm “computer” includes a cloud computer, in particular a cloud server.The term “cloud computer” includes a cloud computer system which inparticular comprises a system of at least one cloud computer and inparticular a plurality of operatively interconnected cloud computerssuch as a server farm. Such a cloud computer is preferably connected toa wide area network such as the world wide web (WWW) and located in aso-called cloud of computers which are all connected to the world wideweb. Such an infrastructure is used for “cloud computing”, whichdescribes computation, software, data access and storage services whichdo not require the end user to know the physical location and/orconfiguration of the computer delivering a specific service. Inparticular, the kiln “cloud” is used in this respect as a metaphor forthe Internet (world wide web). In particular, the cloud providescomputing infrastructure as a service (IaaS). The cloud computer canfunction as a virtual host for an operating system and/or dataprocessing application which is used to execute the method of theinvention. The cloud computer is for example an elastic compute cloud(EC2) as provided by Amazon Web Services™. A computer in particularcomprises interfaces in order to receive or output data and/or performan analogue-to-digital conversion. The data are in particular data whichrepresent physical properties and/or which are generated from technicalsignals. The technical signals are in particular generated by means of(technical) detection devices (such as for example devices for detectingmarker devices) and/or (technical) analytical devices (such as forexample devices for performing imaging methods), wherein the technicalsignals are in particular electrical or optical signals. The technicalsignals in particular represent the data received or outputted by thecomputer. The computer is preferably operatively coupled to a displaydevice which allows information outputted by the computer to bedisplayed, for example to a user. One example of a display device is anaugmented reality device (also referred to as augmented reality glasses)which can be used as “goggles” for navigating. A specific example ofsuch augmented reality glasses is Google Glass (a trademark of Google,Inc.). An augmented reality device can be used both to input informationinto the computer by user interaction and to display informationoutputted by the computer.

The expression “acquiring data” in particular encompasses (within theframework of a data processing method) the scenario in which the dataare determined by the data processing method or program. Determiningdata in particular encompasses measuring physical quantities andtransforming the measured values into data, in particular digital data,and/or computing the data by means of a computer and in particularwithin the framework of the method in accordance with the invention. Themeaning of “acquiring data” also in particular encompasses the scenarioin which the data are received or retrieved by the data processingmethod or program, for example from another program, a previous methodstep or a data storage medium, in particular for further processing bythe data processing method or program. The expression “acquiring data”can therefore also for example mean waiting to receive data and/orreceiving the data. The received data can for example be inputted via aninterface. The expression “acquiring data” can also mean that the dataprocessing method or program performs steps in order to (actively)receive or retrieve the data from a data source, for instance a datastorage medium (such as for example a ROM, RAM, database, hard drive,etc.), or via the interface (for instance, from another computer or anetwork). The data can be made “ready for use” by performing anadditional step before the acquiring step. In accordance with thisadditional step, the data are generated in order to be acquired. Thedata are in particular detected or captured (for example by ananalytical device). Alternatively or additionally, the data are inputtedin accordance with the additional step, for instance via interfaces. Thedata generated can in particular be inputted (for instance into thecomputer). In accordance with the additional step (which precedes theacquiring step), the data can also be provided by performing theadditional step of storing the data in a data storage medium (such asfor example a ROM, RAM, CD and/or hard drive), such that they are readyfor use within the framework of the method or program in accordance withthe invention. The step of “acquiring data” can therefore also involvecommanding a device to obtain and/or provide the data to be acquired. Inparticular, the acquiring step does not involve an invasive step whichwould represent a substantial physical interference with the body,requiring professional medical expertise to be carried out and entailinga substantial health risk even when carried out with the requiredprofessional care and expertise. In particular, the step of acquiringdata, in particular determining data, does not involve a surgical stepand in particular does not involve a step of treating a human or animalbody using surgery or therapy. In order to distinguish the differentdata used by the present method, the data are denoted (i.e. referred to)as “XY data” and the like and are defined in terms of the informationwhich they describe, which is then preferably referred to as “XYinformation” and the like.

Image fusion can be elastic image fusion or rigid image fusion. In thecase of rigid image fusion, the relative position between the pixels ofa 2D image and/or voxels of a 3D image is fixed, while in the case ofelastic image fusion, the relative positions are allowed to change.

In this application, the term “image morphing” is also used as analternative to the term “elastic image fusion”, but with the samemeaning.

Elastic fusion transformations (for example, elastic image fusiontransformations) are in particular designed to enable a seamlesstransition from one dataset (for example a first dataset such as forexample a first image) to another dataset (for example a second datasetsuch as for example a second image). The transformation is in particulardesigned such that one of the first and second datasets (images) isdeformed, in particular in such a way that corresponding structures (inparticular, corresponding image elements) are arranged at the sameposition as in the other of the first and second images. The deformed(transformed) image which is transformed from one of the first andsecond images is in particular as similar as possible to the other ofthe first and second images. Preferably, (numerical) optimisationalgorithms are applied in order to find the transformation which resultsin an optimum degree of similarity. The degree of similarity ispreferably measured by way of a measure of similarity (also referred toin the following as a “similarity measure”). The parameters of theoptimisation algorithm are in particular vectors of a deformation field.These vectors are determined by the optimisation algorithm in such a wayas to result in an optimum degree of similarity. Thus, the optimumdegree of similarity represents a condition, in particular a constraint,for the optimisation algorithm. The bases of the vectors lie inparticular at voxel positions of one of the first and second imageswhich is to be transformed, and the tips of the vectors lie at thecorresponding voxel positions in the transformed image. A plurality ofthese vectors are preferably provided, for instance more than twenty ora hundred or a thousand or ten thousand, etc. Preferably, there are(other) constraints on the transformation (deformation), in particularin order to avoid pathological deformations (for instance, all thevoxels being shifted to the same position by the transformation). Theseconstraints include in particular the constraint that the transformationis regular, which in particular means that a Jacobian determinantcalculated from a matrix of the deformation field (in particular, thevector field) is larger than zero, and also the constraint that thetransformed (deformed) image is not self-intersecting and in particularthat the transformed (deformed) image does not comprise faults and/orruptures. The constraints include in particular the constraint that if aregular grid is transformed simultaneously with the image and in acorresponding manner, the grid is not allowed to interfold at any of itslocations. The optimising problem is in particular solved iteratively,in particular by means of an optimisation algorithm which is inparticular a first-order optimisation algorithm, in particular agradient descent algorithm. Other examples of optimisation algorithmsinclude optimisation algorithms which do not use derivations, such asthe downhill simplex algorithm, or algorithms which use higher-orderderivatives such as Newton-like algorithms. The optimisation algorithmpreferably performs a local optimisation. If there are a plurality oflocal optima, global algorithms such as simulated annealing or genericalgorithms can be used. In the case of linear optimisation problems, thesimplex method can for instance be used.

In the steps of the optimisation algorithms, the voxels are inparticular shifted by a magnitude in a direction such that the degree ofsimilarity is increased. This magnitude is preferably less than apredefined limit, for instance less than one tenth or one hundredth orone thousandth of the diameter of the image, and in particular aboutequal to or less than the distance between neighbouring voxels. Largedeformations can be implemented, in particular due to a high number of(iteration) steps.

The determined elastic fusion transformation can in particular be usedto determine a degree of similarity (or similarity measure, see above)between a first and a second dataset (first and second images). To thisend, the deviation between the elastic fusion transformation and anidentity transformation is determined The degree of deviation can forinstance be calculated by determining the difference between thedeterminant of the elastic fusion transformation and the identitytransformation. The higher the deviation, the lower the similarity,hence the degree of deviation can be used to determine a measure ofsimilarity.

A measure of similarity can in particular be determined on the basis ofa determined correlation between the first and second datasets.

It is the function of a marker to be detected by a marker detectiondevice (for example, a camera or an ultrasound receiver or analyticaldevices such as CT or MRI devices) in such a way that its spatialposition (i.e. its spatial location and/or alignment) can beascertained. The detection device is in particular part of a navigationsystem. The markers can be active markers. An active marker can forexample emit electromagnetic radiation and/or waves which can be in theinfrared, visible and/or ultraviolet spectral range. A marker can alsohowever be passive, i.e. can for example reflect electromagneticradiation in the infrared, visible and/or ultraviolet spectral range orcan block x-ray radiation. To this end, the marker can be provided witha surface which has corresponding reflective properties or can be madeof metal in order to block the x-ray radiation. It is also possible fora marker to reflect and/or emit electromagnetic radiation and/or wavesin the radio frequency range or at ultrasound wavelengths. A markerpreferably has a spherical and/or spheroid shape and can therefore bereferred to as a marker sphere; markers can however also exhibit acornered, for example cubic, shape.

A navigation system is understood to mean a system which can comprise:at least one marker device; a transmitter which emits electromagneticwaves and/or radiation and/or ultrasound waves; a receiver whichreceives electromagnetic waves and/or radiation and/or ultrasound waves;and an electronic data processing device which is connected to thereceiver and/or the transmitter, wherein the data processing device (forexample, a computer) in particular comprises a processor (CPU) and aworking memory and advantageously an indicating device for issuing anindication signal (for example, a visual indicating device such as amonitor and/or an audio indicating device such as a loudspeaker and/or atactile indicating device such as a vibrator) and a permanent datamemory, wherein the data processing device processes navigation dataforwarded to it by the receiver and can advantageously output guidanceinformation to a user via the indicating device. The navigation data canbe stored in the permanent data memory and for example compared withdata stored in said memory beforehand.

The movements of the treatment body parts are in particular due tomovements which are referred to in the following as “vital movements”.Reference is also made in this respect to EP 2 189 943 A1 and EP 2 189940 A1, also published as US 2010/0125195 A1 and US 2010/0160836 A1,respectively, which discuss these vital movements in detail. In order todetermine the position of the treatment body parts, analytical devicessuch as x-ray devices, CT devices or MRT devices are used to generateanalytical images (such as x-ray images or MRT images) of the body.Analytical devices use imaging methods in particular and are inparticular devices for analyzing a patient's body, for instance by usingwaves and/or radiation and/or energy beams, in particularelectromagnetic waves and/or radiation, ultrasound waves and/orparticles beams. Analytical devices are in particular devices whichgenerate images (for example, two-dimensional or three-dimensionalimages) of the patient's body (and in particular of internal structuresand/or anatomical parts of the patient's body) by analysing the body.Analytical devices are in particular used in medical diagnosis, inparticular in radiology. However, it can be difficult to identify thetreatment body part within the analytical image. It can in particular beeasier to identify an indicator body part which correlates with changesin the position of the treatment body part and in particular themovement of the treatment body part. Tracking an indicator body partthus allows a movement of the treatment body part to be tracked on thebasis of a known correlation between the changes in the position (inparticular the movements) of the indicator body part and the changes inthe position (in particular the movements) of the treatment body part.As an alternative to or in addition to tracking indicator body parts,marker devices (which can be used as an indicator and thus referred toas “marker indicators”) can be tracked using marker detection devices.The position of the marker indicators has a known (predetermined)correlation with (in particular, a fixed relative position relative to)the position of indicator structures (such as the thoracic wall, forexample true ribs or false ribs, or the diaphragm or intestinal walls,etc.) which in particular change their position due to vital movements.

The present invention relates to the field of controlling a treatmentbeam. The treatment beam treats body parts which are to be treated andwhich are referred to in the following as “treatment body parts”. Thesebody parts are in particular parts of a patient's body, i.e. anatomicalbody parts.

A treatment beam treats body parts which are to be treated and which arereferred to as “treatment body parts” or “target regions”. These bodyparts are in particular parts of a patient's body, i.e. anatomical bodyparts. Ionizing radiation is in particular used for the purpose oftreatment. In particular, the treatment beam comprises or consists ofionizing radiation. The ionizing radiation comprises or consists ofparticles (for example, sub-atomic particles or ions) or electromagneticwaves which are energetic enough to detach electrons from atoms ormolecules and so ionize them. Examples of such ionizing radiationinclude x-rays, high-energy particles (high-energy particle beams)and/or ionizing radiation emitted from a radioactive element. Thetreatment radiation, in particular the treatment beam, is in particularused in radiation therapy or radiotherapy, in particular in the field ofoncology. For treating cancer in particular, parts of the bodycomprising a pathological structure or tissue such as a tumour aretreated using ionizing radiation. The tumour is then an example of atreatment body part.

The treatment beam is preferably controlled such that it passes throughthe treatment body part. However, the treatment beam can have a negativeeffect on body parts outside the treatment body part. These body partsare referred to here as “outside body parts”. Generally, a treatmentbeam has to pass through outside body parts in order to reach and sopass through the treatment body part.

Reference is also made in this respect to the following web pages:http://www.elekta.com/healthcare_us_elekta_vmat.php andhttp://www.varian.com/us/oncology/treatments/treatment_techniques/rapidarc.

In the field of medicine, imaging methods (also called imagingmodalities and/or medical imaging modalities) are used to generate imagedata (for example, two-dimensional or three-dimensional image data) ofanatomical structures (such as soft tissues, bones, organs, etc.) of thehuman body. The term “medical imaging methods” is understood to mean(advantageously apparatus-based) imaging methods (so-called medicalimaging modalities and/or radiological imaging methods) such as forinstance computed tomography (CT) and cone beam computed tomography(CBCT, in particular volumetric CBCT), x-ray tomography, magneticresonance tomography (MRT or MRI), conventional x-ray, sonography and/orultrasound examinations, and positron emission tomography. Analyticaldevices in particular are used to generate the image data inapparatus-based imaging methods. The imaging methods are in particularused for medical diagnostics, to analyze the anatomical body in order togenerate images which are described by the image data. The imagingmethods are also in particular used to detect pathological changes inthe human body. However, some of the changes in the anatomicalstructure, in particular the pathological changes in the structures(tissue), may not be detectable and in particular may not be visible inthe images generated by the imaging methods. A tumour represents anexample of a change in an anatomical structure. If the tumour grows, itmay then be said to represent an expanded anatomical structure. Thisexpanded anatomical structure may not be detectable; in particular, onlya part of the expanded anatomical structure may be detectable.Primary/high-grade brain tumours are for example usually visible on MRIscans when contrast agents are used to infiltrate the tumour. MRI scansrepresent an example of an imaging method. In the case of MRI scans ofsuch brain tumours, the signal enhancement in the MRI images (due to thecontrast agents infiltrating the tumour) is considered to represent thesolid tumour mass. Thus, the tumour is detectable and in particulardiscernible in the image generated by the imaging method. In addition tothese tumours, referred to as “enhancing” tumours, it is thought thatapproximately 10% of brain tumours are not discernible on a scan and arein particular not visible to a user looking at the images generated bythe imaging method.

DESCRIPTION OF THE FIGURES

In the following, the invention is described with reference to theenclosed figures which represent at least preferred embodiment of theinvention. The scope of the invention is however not limited to thespecific features disclosed in the figures and described in connectionwith the figures.

FIG. 1 shows a treatment device usable for conducting the invention;

FIG. 2 is a flow diagram showing the functionality of the method inaccordance with the invention; and

FIGS. 3A to 3C show screenshots from a prototype software applicationimplementing the disclosed method.

According to FIG. 1, the treatment device (which can be a radiotherapyor radiosurgery device) comprises at least a patient support deviceembodied by a treatment table 5, an imaging unit comprising an x-raytube 8 and an x-ray detector 7, and a treatment unit embodied by alinear accelerator 9 which is configured to emit a treatment beamcomprising ionizing treatment radiation onto the anatomical body partrepresented by the patient's lung 2. A patient 1 having the anatomicalbody part is placed on the patient support device embodied by thetreatment table 5 which can be moved by a moving unit embodied by anelectric motor 6. The treatment table 5 is placed under the treatmentunit. The curved arrow indicates that the linear accelerator 9 can berotated around the patient's longitudinal axis. A headrest 3 made from acarbon material is placed adjacent to (in particular under) thepatient's head in order to support the patient's head. The base plate ofthe headrest 3 is shown in FIG. 1 out of perspective and merely forreasons of illustration. A marker device (for example in the shape of aframe or a belt) comprising a plurality of markers 4 is disposed on thepatient's thorax, in the case of FIG. 1 three markers 4 a are used. Thespatial relationship between the markers 4 and the headrest 3 is knownand fixed. The treatment device also comprises a computer 11 which ispart of a navigation system 10. The computer 11 comprises a volatilememory such as a RAM 14, a non-volatile memory embodied by a hard disc13 and a processing unit embodied by microprocessor 12. Furthermore, thecomputer 11 is operatively coupled to an input unit embodied by akeyboard 15 and a visual output unit such as a monitor 16. Thenavigation system also comprises a transmitter of the navigation systemembodied by infrared transmitters 17 and a receiver embodied byinfrared-sensitive stereoscopic camera 18 which are both operativelycoupled to the computer 11. The computer 11 is also configured tocontrol the other parts of the treatment device such as the imaging unitand the treatment unit and the moving unit. The treatment unit isoperatively coupled to the computer 11 in order to receive, from thecomputer 11, control signals for activating the treatment beam independence on the current movement phase data as explained above.

FIG. 2 shows a flow diagram comprising exemplary steps of theabove-described data processing method.

In the flow diagram of FIG. 2 and the screenshots of FIGS. 3A to C, theanatomical body part is a lung tumour and the vital movement is thebreathing movement of the patient's thorax.

In particular, steps 1) and 2) relate to generating and acquiring theadvance medical image data embodied by a stereo-fluoro-sequence (i.e.sequence of pairs of fluoroscopic images which have been taken inparticular in directions which—in three-dimensional space—areperpendicular to each other). In step 1), retroreflective markers areattached to the patient's chest and tracked using an infrared trackingcamera 18 to produce a breathing curve for the patient 1. In step 2),the stereo-fluoro-sequence is taken prior to the treatment. Time-stampsynchronization is used to time-correlate the current medical image dataembodied by the fluoro-sequence. Thereby, the fluoro-sequence isregistered to the breathing curve.

In step 3), the advance medical image data is acquired. In the case ofFIG. 2, a planning CT of only one specific respiratory state (i.e.specific movement phase) is used as the advance medical image. From theplanning CT, a pair of digitally radiographs (DRRs) of the target regionand/or indicators for the position of the target region are rendered.These DRRs are fused in step 4) to that x-ray image pair in thestereo-fluoro-sequence (which embodies the sequence of current medicalimages) which originates from the at least substantially samerespiratory state as the respiratory with which the planning CT isassociated. Step 5) encompasses determination of the specific imagesubset data and the subset tracking data by using a matched counterpartembodied by two selections, e.g. cutouts (clippings), from the x-rayimage pair for mono-modal detection of the target position (i.e. of theposition of the target region) in the remaining image pairs (i.e. in theremaining current medical images), in particular in the at least onetracking current medical image of the sequence of current medical imagesembodied by the fluoro-sequence.

Optional step 6) relates to building a correlation model between theexternal breathing curve generated for generating the advance medicalimage data (the planning CT and the internal position of the targetregion which may be embodied by the anatomical body part). Thus, aninternal breathing curve can be established. Such an internal breathingcurve may serve as a basis for issuing the control signals to thetreatment unit for activating or de-activating the treatment beam.

FIGS. 3A to 3C are screenshots gathered from a prototype softwareapplication for implementing the disclosed data processing method. FIG.3A shows in its left half three views from three different spatialdirections in which the specific image subset is defined for example bymanually clipping a rectangular region in the centre of one of theviews, i.e. by user input. The application automatically clips acorresponding region in the two other views by transformation of thecoordinates from the manually edited view into the coordinates of theother two views. The three views shown in FIG. 3A are the axial, thecoronal and the sagittal view of the planning CT of the tumour. In theright half of FIG. 3A, a preview of a pair of DRRs is given which show astereo-imaging view of the image region selected (clipped) in one of theviews in the left half of FIG. 3A.

FIG. 3B shows a fusion of the DRRs generated as explained with regard toFIG. 3A with the x-ray image pair which has been determined as thespecific current medical image. Based on comparing the DRRs to the x-rayimage pair, the region in the x-ray image pair representing the specificimage subset can be determined and highlighted by placing a rectangularframe around it as shown in FIG. 3C. The rectangular frame shown in FIG.3C therefore is an example of the above-described graphical featuredefined by the display marking data.

1.-15. (canceled)
 16. A system, comprising a computer having a processorconfigured to execute a computer-implemented method of determining therepresentation of an anatomical body part of a patient in a sequence ofmedical images, the anatomical body part being subject to a vitalmovement of the patient, the method comprising executing, on theprocessor of the computer, steps of: acquiring, at the processor,advance medical image data comprising a time-related advance medicalimage having a representation of the anatomical body part in a specificmovement phase; acquiring, at the processor, current medical image datadescribing a sequence of current medical images, wherein the sequencecomprises a specific current medical image comprising a representationof the anatomical body part in the specific movement phase, and atracking current medical image which is different from the specificcurrent medical image and comprises a representation of the anatomicalbody part in a tracking movement phase which is different from thespecific movement phase; determining, by the processor and based on theadvance medical image data and the current medical image data, specificimage subset data describing a specific image subset of the specificcurrent medical image, the specific image subset comprising therepresentation of the anatomical body part; determining, by theprocessor and based on the current medical image data and the specificimage subset data, subset tracking data describing a tracked imagesubset in the tracking current medical image, the tracked image subsetcomprising the representation of the anatomical body part.
 17. Acomputer-implemented method of determining the representation of ananatomical body part of a patient in a sequence of medical images, theanatomical body part being subject to a vital movement of the patient,the method comprising executing, on a processor of the computer, stepsof: acquiring, at the processor, advance medical image data comprising atime-related advance medical image comprising a representation of theanatomical body part in a specific movement phase; acquiring, at theprocessor, current medical image data describing a sequence of currentmedical images, wherein the sequence comprises a specific currentmedical image comprising a representation of the anatomical body part inthe specific movement phase, and a tracking current medical image whichis different from the specific current medical image and comprises arepresentation of the anatomical body part in a tracking movement phasewhich is different from the specific movement phase; determining, by theprocessor and based on the advance medical image data and the currentmedical image data, specific image subset data describing a specificimage subset of the specific current medical image, the specific imagesubset comprising the representation of the anatomical body part;determining, by the processor and based on the current medical imagedata and the specific image subset data, subset tracking data describinga tracked image subset in the tracking current medical image, thetracked image subset comprising the representation of the anatomicalbody part.
 18. The method according to claim 17, comprising a step ofacquiring, at the processor, current movement phase data describing acurrent movement phase of the anatomical body part in the states inwhich it is described by the sequence of current medical images, whereinthe current movement phase data is generated based on acquiring digitalsignals describing the vital movement which have been generated based ontracking marker devices attached to the patient's body and correlatingthe result of the tracking with the current medical image data, whereinthe specific current medical image is determined, by the processor,based on the current movement phase data.
 19. The method according toclaim 17, wherein the specific image subset data describes the positionof the specific image subset in the specific current medical image, andwherein the subset tracking data describes the position of the trackedimage subset in the tracking current medical image.
 20. The methodaccording to claim 19, comprising a step of determining, by theprocessor and based on the current medical image data and the subsettracking data and the current movement phase data, internal breathingcurve data describing a time-correlation of the image positions of theanatomical body part and the sequence of current medical images.
 21. Themethod according to claim 17, wherein the specific image subset data isdetermined, by the processor, based on determining, by the processor, acorresponding representation of the anatomical body part in the advancemedical image and in the sequence of current medical images.
 22. Themethod according to claim 21, comprising a step of acquiring, at theprocessor, current medical image user input data describing an input bya user for selecting the specific image subset from the specific currentmedical image wherein the image subset data is determined, by theprocessor, based on the user input data.
 23. The method according toclaim 17, comprising a step of acquiring, at the processor, advanceimage subset data describing an advance image subset of the advancemedical image comprising the representation of the anatomical body part,wherein the specific image subset data is determined, by the processor,based on the advance image subset data.
 24. The method according toclaim 23, comprising a step of acquiring, at the processor, advancemedical image user input data describing an input by a user forselecting the advance image subset from the advance medical image,wherein the advance image subset data is determined, by the processor,based on the advance medical image user input data.
 25. The methodaccording to claim 23, wherein the advance image subset data isdetermined based on automatic determination of the advance image subset,for example by applying an image segmentation algorithm to the advancemedical image.
 26. The method according to claim 22, wherein thespecific image subset data is determined, by the processor, based on theresult of comparing the advance image subset data to the specificcurrent medical image.
 27. The method according to claim 17, wherein thesubset tracking data is determined by determining, by the processor, aregion in the tracking current medical image which is at least to apredetermined degree comparable to the specific image subset.
 28. Themethod according to claim 17, wherein the advance medical image data hasbeen generated by applying a computed tomography imaging method to thepatient's body, wherein the advance medical image is a digitallyrendered radiograph rendered from the computed tomography of thepatient's body, and wherein the sequence of current medical images hasbeen generated by applying a conventional x-ray imaging method.
 29. Anon-transitory computer-readable program storage medium storing aprogram, which, when executed on a processor of a computer or whenloaded into a memory of the computer, causes the computer to perform acomputer-implemented method of determining the representation of ananatomical body part of a patient in a sequence of medical images, theanatomical body part being subject to a vital movement of the patient,the method comprising executing, on the processor of the computer, stepsof: acquiring, at the processor, advance medical image data comprising atime-related advance medical image comprising a representation of theanatomical body part in a specific movement phase; acquiring, at theprocessor, current medical image data describing a sequence of currentmedical images, wherein the sequence comprises a specific currentmedical image comprising a representation of the anatomical body part inthe specific movement phase, and a tracking current medical image whichis different from the specific current medical image and comprises arepresentation of the anatomical body part in a tracking movement phasewhich is different from the specific movement phase; determining, by theprocessor and based on the advance medical image data and the currentmedical image data, specific image subset data describing a specificimage subset of the specific current medical image, the specific imagesubset comprising the representation of the anatomical body part;determining, by the processor and based on the current medical imagedata and the specific image subset data, subset tracking data describinga tracked image subset in the tracking current medical image, thetracked image subset comprising the representation of the anatomicalbody part.
 30. A treatment device, comprising: a computer having amemory and instructions stored thereon, the instructions, when executedby one or more processors of the computer, causing the computer todetermine the representation of an anatomical body part of a patient ina sequence of medical images, the anatomical body part being subject toa vital movement of the patient, the computer, when executing theinstructions, further implements the steps of: acquiring, at theprocessor, advance medical image data comprising a time-related advancemedical image comprising a representation of the anatomical body part ina specific movement phase; acquiring, at the processor, current medicalimage data describing a sequence of current medical images, wherein thesequence comprises a specific current medical image comprising arepresentation of the anatomical body part in the specific movementphase, and a tracking current medical image which is different from thespecific current medical image and comprises a representation of theanatomical body part in a tracking movement phase which is differentfrom the specific movement phase; determining, by the processor andbased on the advance medical image data and the current medical imagedata, specific image subset data describing a specific image subset ofthe specific current medical image, the specific image subset comprisingthe representation of the anatomical body part; determining, by theprocessor and based on the current medical image data and the specificimage subset data, subset tracking data describing a tracked imagesubset in the tracking current medical image, the tracked image subsetcomprising the representation of the anatomical body part. a medicalimaging device for acquiring the current medical image data; anirradiation unit for emitting a treatment beam to the patient's body,wherein the computer is operatively coupled to the medical imagingdevice to acquire the current medical image data and to the irradiationunit to issue control signals for emitting the treatment beam.